Smarter genetic tools for tracking infectious germs
Tree-based population genetics methods for genetic epidemiology
This project builds smarter genetic tools that help public health teams and patients see how infections spread and change over time.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cornell University NIH-funded |
| Lab location | 1 site (Ithaca, United States) |
| Project ID | NIH-11251953 on NIH RePORTER |
What this research studies
Researchers will create new computer and statistical methods that use pathogen DNA or RNA to reconstruct how infections move and evolve. The work will model realistic features like dormant infections and mixed (polyclonal) infections and will combine genealogy-based approaches with epidemiological models. New algorithms will be developed and tested on genetic datasets and surveillance samples to handle these complexities. The goal is to make genetic surveillance more accurate and usable for public health decisions.
Who could benefit from this research
Good fit: Ideal participants are people whose infections have been genetically sequenced or who can provide pathogen samples through public health or hospital surveillance.
Not a fit: People without infectious diseases or those not part of genetic surveillance programs are unlikely to see direct benefit.
Why it matters
Potential benefit: If successful, this could lead to faster and more accurate outbreak detection and help guide treatments and public health actions.
How similar studies have performed: Other genomic and phylodynamic methods have improved outbreak tracing before, but applying seedbank and metapopulation theories to dormant and mixed infections is a novel advance.
Where this research is happening
Ithaca, United States
- Cornell University — Ithaca, United States (Active)
Researchers
- Principal investigator: Kim, Jaehee — Cornell University
- Study coordinator: Kim, Jaehee
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.